CN111182649A - Random access method based on large-scale MIMO - Google Patents

Random access method based on large-scale MIMO Download PDF

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CN111182649A
CN111182649A CN202010003901.1A CN202010003901A CN111182649A CN 111182649 A CN111182649 A CN 111182649A CN 202010003901 A CN202010003901 A CN 202010003901A CN 111182649 A CN111182649 A CN 111182649A
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users
random access
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CN111182649B (en
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吴哲夫
陈明达
黄巍
王中友
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Zhejiang University of Technology ZJUT
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
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    • H04W74/00—Wireless channel access
    • H04W74/08—Non-scheduled access, e.g. ALOHA
    • H04W74/0833—Random access procedures, e.g. with 4-step access
    • H—ELECTRICITY
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Abstract

A random access method based on massive MIMO comprises the following steps: 1. a user selects a random access block and sends a random access request to a base station; 2. a base station end estimates the number of users in a given time domain resource, and estimates the timing offset and frequency domain code identification of each user; 3. using the obtained parameters to carry out corresponding estimation of the channel; 4. judging whether the user needs to retransmit, recording the retransmitted user, and retransmitting the user to initiate a random access request again; 5. performing corresponding estimation on a second channel, and recording the number of users successfully requesting; 6. the random access is ended. Under the condition of considering frequency error and time error, the invention improves the problem that the existing method is limited by the frequency domain resource number N in the aspect of estimating the user number to a certain extent, and also greatly improves the aspects of estimating the time error and channel information of the user.

Description

Random access method based on large-scale MIMO
Technical Field
The invention belongs to the technical field of communication, and further relates to a random access method based on large-scale MIMO in the wireless communication technology. Under the condition of considering frequency error and time error, the problem that the prior method is limited by the frequency domain resource number N in the aspect of estimating the number of users is improved to a certain extent, and the time error and the channel information of the estimated users are also greatly improved.
Background
The Multiple-Input Multiple-Output (MIMO) technology is to use Multiple transmitting antennas and Multiple receiving antennas at a transmitting end and a receiving end, respectively, to fully utilize space resources, and improve channel capacity of a system without increasing spectrum resources and antenna transmitting power. The massive MIMO technology is an improvement based on the MIMO technology, and performance superior to the MIMO technology is obtained by configuring tens or even hundreds of antennas at a hub. In a massive MIMO system aiming at H2H (Human To Human) users, a dedicated pilot frequency can be allocated To each user, and the orthogonality of the pilot frequencies can enable a set station To accurately estimate channel information from the users To a base station. However, in the M2M (Machine To Machine) scenario, the number of users is much greater than that in the H2H scenario, and there is a case where multiple users select the same pilot frequency at the same time, which causes pilot frequency pollution.
The problem of pilot pollution can be improved to a certain extent by adopting a pilot random access method. However, in the existing random access scheme, a perfect frequency domain and time synchronization network is mostly considered, so that the orthogonality of the pilot sequence of the random access is preserved at the set station. During random access, frequency errors may be caused by doppler shift and estimation errors during initial downlink synchronization, and time errors may be caused by differences in the locations of users within a cell. In the presence of frequency and time errors, the random access pilots transmitted on adjacent subcarriers and consecutive OFDM symbols will no longer have orthogonality at the set station. The result is a significant degradation in the performance of the random access scheme.
Considering frequency and time errors, Luca Sanguinetti et al propose a new Random Access scheme in Random Access in massive MIMO by applying Timing Offsets and external Antennas, which mainly comprises the following steps: firstly, selecting a pair of random access codes for an active user to enter and sending the random access codes to a base station; then, the base station estimates the number of users of each time domain resource by using an MDL algorithm, estimates the timing offset of the users and calculates channel estimation; judging whether the user needs to retransmit by using an SUCR protocol; finally, channel estimation is used to distinguish two users with similar time offsets. However, the number of users used in the method for estimating the number of users is limited to a great extent by the number of frequency domain resources, and once the number of users selecting the same time domain resource is greater than the number of frequency domain resources, the estimated number of users, time offset and channel information have great deviation, and the number of users retransmitting pilot frequency is also reduced.
Disclosure of Invention
In order to overcome the defects of the existing method, the invention provides a random access method based on large-scale MIMO, under the condition of considering frequency error and time error, the problem that the existing method is limited by the frequency domain resource number N in the aspect of estimating the number of users is improved to a certain extent, and the time error and channel information of the users are also greatly improved in the aspect of estimating.
In order to achieve the above-mentioned goal, the invention adopts the technical scheme that:
a random access method based on massive MIMO comprises the following steps:
step 1: for a given user wanting to access the network in a cell, the user respectively forms a time domain and frequency domain random access block from time domain resources and frequency domain resource selection codes, sends a random access request to a base station, for the random access block, the random access block consists of Q continuous OFDM symbols and N adjacent subcarriers, the total is tau samples, wherein tau is QN, and after downlink synchronization, for a given active user wanting to access the network, the user randomly selects C from CQ＝{t0,t1,…,tQ-1And CN＝{f0,f1,…,fN-1Selecting a pair of code blocks, wherein
Figure BDA0002354505580000031
Represents a frequency domain resource block,
Figure BDA0002354505580000032
Representing time domain resource blocks, using lkE {0,1 …, N-1} and ikE {0,1 …, Q-1} to represent the code block index selected by user k;
step 2: the base station estimates the number of activated users selecting the same time domain resource, and in the process of random access, the following facts are utilized: the orthogonality of time domain codes can not be destroyed by a propagation channel, and mutual interference can not be generated between users selecting different time domain codes, so that under the condition of not losing generality, users selecting the same time domain resource can only be concerned, and the process is as follows:
step 2.1: the base station receives the received signal matrix of the active user
Figure BDA0002354505580000033
The DFT output matrix of the mth antenna is represented as:
Figure BDA0002354505580000034
where K represents the set of users, ρkRepresenting the transmit power, h, of user kkmRepresenting the channel transmission coefficient from user k to antenna m,
Figure BDA0002354505580000035
for the effective timing offset of user k,
Figure BDA0002354505580000036
is the effective frequency-domain code of user k, t represents the current time-domain resource block,
Figure BDA0002354505580000037
and WmRespectively representing inter-cell interference and thermal noise, and T represents the transposition of a matrix;
step 2.2: associating the received signal matrix with the current time domain resource allows to estimate the number of users selecting the current time domain resource.
Figure BDA0002354505580000038
Figure BDA0002354505580000039
Wherein
Figure BDA00023545055800000310
The representation of the noise is represented by,
Figure BDA00023545055800000311
represents the effective channel transmission coefficient of user k at antenna m, | | | | | represents the euclidean norm, | represents the conjugate of the matrix,
Figure BDA0002354505580000041
to NaRounding off can be carried out to obtain the user number estimated value for selecting the current time domain resource
Figure BDA0002354505580000042
And step 3: performing frequency domain resource code identification and timing offset estimation on all users, wherein the process comprises the following steps:
step 3.1: estimating the timing offset of all estimated users by utilizing a method for estimating the timing offset;
the estimated number of users obtained in step 2.2
Figure BDA0002354505580000043
To is directed at
Figure BDA0002354505580000044
Dividing users into two parts to calculate user's timing offset, if the number of users
Figure BDA0002354505580000045
Then divide the user into front
Figure BDA0002354505580000046
After being combined
Figure BDA0002354505580000047
To before
Figure BDA0002354505580000048
The individual user estimates the timing offset using the ESPRIT algorithm, and thereafter
Figure BDA0002354505580000049
The method for estimating the timing offset of each user is used for acquiring the timing offset value of each user by an offset estimation method, and the estimated timing offset and the effective frequency domain code of all the estimated users are acquired and respectively expressed as follows:
Figure BDA00023545055800000410
Figure BDA00023545055800000411
step 3.2, the frequency domain resource code selected by the user is obtained by utilizing the obtained timing offset estimation value;
and 4, step 4: the base station end estimates the channel response of the user, and the process is as follows:
step 4.1: acquiring a channel response estimation value of an estimated user by using the parameters acquired in the step 3, wherein the channel response estimation value is represented as:
Figure BDA00023545055800000412
where | · | | represents the euclidean norm, represents the conjugate of the matrix;
step 4.2: and judging whether the estimated value has errors in the step 3 according to the channel response estimated value.
Using the channel response estimates obtained in step 4.1, the per-user estimates are calculated
Figure BDA0002354505580000051
If there is a user
Figure BDA0002354505580000052
If 0 is obtained, this indicates thatThe offset value of the user is estimated erroneously;
step 4.3: if the user with the error estimation exists, re-estimating the timing offset and the frequency domain code for the user with the error estimation;
step 4.4: acquiring the channel response estimation values of all estimated users again, recording the users which can be successfully detected, judging whether users needing to be retransmitted exist or not, and recording the channel response estimation values acquired again as
Figure BDA0002354505580000053
Computing
Figure BDA0002354505580000054
If Num of user kkIf the number of the users is more than 1, the users and the user are proved to be positioned in the same random access block, the timing offsets of the users are very small, the models are difficult to distinguish, and the users are recorded for retransmission;
and 5: and for the retransmission user base station, performing second channel response estimation, wherein the process is as follows:
step 5.1: repeating the steps 2-4.3 for the users needing to be retransmitted in the step 4.4;
step 5.2: acquiring a channel response estimation value aiming at a retransmission user, and recording the number of users which can be successfully detected after retransmission;
step 5.3: recording the users successfully detected in the step 4.4 and the step 5.2;
step 6: the random access procedure ends.
Further, in step 1, for an active user selectable random access block, which consists of Q consecutive OFDM symbols and N adjacent subcarriers, there are a total of τ samples, where τ is QN.
Still further, in step 2, since the orthogonality of the time domain codes is not destroyed by the propagation channel, users selecting different time domain codes will not interfere with each other.
Still further, in step 2, the base station obtains the received informationNumber is
Figure BDA0002354505580000061
Which represents the DFT output matrix for the mth antenna of the base station,
Figure BDA0002354505580000062
associated with the current time domain resource, the user number of the current time domain resource can be estimated
Figure BDA0002354505580000063
In step 3, before timing offset estimation and frequency domain code identification are performed on the estimated user, the number of estimated users needs to be determined
Figure BDA0002354505580000064
And for the size relation with the N-1, respectively adopting different algorithms to estimate the timing offset of the users for the users less than or equal to the N-1 and the users more than the N-1, and obtaining the frequency domain codes of the users through the timing offset.
In the step 4.4, if there are two or more users that have the same random access block and their timing offsets have very small differences, the model will be difficult to distinguish the two users, so according to the estimated user channel information, it can be determined whether there are multiple users that cannot be distinguished, record the users that cannot be distinguished and resend them, the retransmitted user repeats the steps 1 to 4, and finally the base station re-estimates the channel response of the retransmitted user.
The invention has the beneficial effects that:
1. compared with the conventional random access scheme, the present invention takes into account frequency errors and time errors during random access.
2. The invention provides a new user number estimation method, which solves the problem that the existing method is limited by the frequency domain resource number N in the aspect of estimating the user number to a certain extent, and also greatly improves the aspects of estimating the time error and the channel information of the user.
Drawings
FIG. 1 is a flow chart of the present invention;
fig. 2 and 3 are simulation graphs of the results of the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and the specific examples.
Referring to fig. 1 to 3, a pilot random access method based on massive MIMO includes the following steps:
step 1: for a given user who wants to enter a network in a cell, the user respectively selects codes from time domain resources and frequency domain resources to form a time domain and frequency domain random access block and sends a random access request to a base stationaProbability is activated to become an activated user, and total number of activated users Na＝K*pa(M＞＞Na) Wherein the random access block consists of Q consecutive OFDM symbols and N adjacent subcarriers, for a total of τ samples, where τ is QN, and after downlink synchronization, for a given active user wanting to access the network, the user randomly selects from CQ＝{t0,t1,…,tQ-1And CN＝{f0,f1,…,fN-1Selecting a pair of code blocks, wherein
Figure BDA0002354505580000071
Represents a frequency domain resource block,
Figure BDA0002354505580000072
Figure BDA0002354505580000073
Representing time domain resource blocks, using lkE {0,1 …, N-1} and ikE {0,1 …, Q-1 }) toCode block index representing user k selection, further assume
Figure BDA0002354505580000074
Wherein the random access signal transmitted from user k to the base station is accompanied by a specific carrier frequency offset omegakAnd normalized timing error thetak. Wherein theta iskDepending on the distance of user k to the base station side, which is denoted as
Figure BDA0002354505580000075
Maximum value of timing error
Figure BDA0002354505580000076
Wherein c is 3x108m/s denotes the speed of light, B is the bandwidth, DkIs the distance from user k to the base station end, DmaxIs the maximum distance;
step 2: the base station estimates the number of activated users selecting the same time domain resource, and the process is as follows:
step 2.1: a base station receives a received signal matrix of an activated user;
during Q OFDM symbols, the DFT output of the mth antenna of the base station on subcarrier n is:
Figure BDA0002354505580000081
where k denotes the set of all active users, pkIs the transmit power of a user, where hkmRepresents the channel transmission coefficient between the user k and the mth antenna at the base station end, and can be determined by large-scale fading and small-scale fading together
Figure BDA0002354505580000082
Wherein g iskmThe method represents that the obedience probability density function between the user k and the ith antenna at the base station end is as follows
Figure BDA0002354505580000083
Small ruler independently and simultaneously distributeddegree of fading coefficient, betakthe method represents the large-scale fading coefficient between a user k and a base station, which is usually related to shadow fading and path loss, and the distance between base station end antennas is generally negligible compared with the transmission distance between the user and the base station, so that the large-scale fading coefficients of any antenna of the user and the base station are both betakMoreover, in order to ensure that the signals received by the base station end have the same power, power control is adopted to ensure that rho is equalkβk＝1，
Figure BDA0002354505580000084
For the effective timing offset of user k, NFFT1024 is the number of samples of the fourier transform,
Figure BDA0002354505580000085
it is indicative of the thermal noise that is,
Figure BDA0002354505580000086
representing inter-cell interference, T representing a transpose of a matrix, further using
Figure BDA0002354505580000087
Representing the DFT output matrix at antenna m;
Figure BDA0002354505580000088
wherein
Figure BDA0002354505580000089
Is the effective frequency domain code of user k;
since the orthogonality of time domain codes is not destroyed by the propagation channel, and mutual interference does not occur between users selecting different time domain codes, the formula (1) can be rewritten to the formula (1) by focusing only on the users selecting the same time domain resource without losing generality
Figure BDA00023545055800000810
Where T represents the transpose of the matrix,k represents the set of active users in a single time domain block, with the index i of the index t removed for simplicityk；
Step 2.2: the received signal matrix is associated with the current time domain resource, the number of users selecting the current time domain resource can be estimated, and the received signal is transmitted
Figure BDA0002354505580000091
Associated with the time domain t, i.e.
Figure BDA0002354505580000092
Figure BDA0002354505580000093
Wherein
Figure BDA0002354505580000094
The representation of the noise is represented by,
Figure BDA0002354505580000095
the effective channel transmission coefficient of a user k at an antenna m is represented, | | · | | | represents an Euclidean norm, and the conjugate of a matrix is represented, so that the user number of the current time domain resource can be estimated according to the gradual most propagation characteristic of a large-scale MIMO system channel
Figure BDA0002354505580000096
To NaIs rounded to obtain the estimated number of users
Figure BDA0002354505580000097
And step 3: performing frequency domain resource code identification and timing offset estimation on all users, wherein the process comprises the following steps:
step 3.1: estimating the timing offset of all estimated users by utilizing a method for estimating the timing offset;
first, a sample correlation matrix is calculated
Figure BDA0002354505580000098
To is directed at
Figure BDA0002354505580000099
Dividing users into two parts to calculate user's timing offset, if the number of users
Figure BDA00023545055800000910
Then divide the user into front
Figure BDA00023545055800000911
After being combined
Figure BDA00023545055800000912
To before
Figure BDA00023545055800000913
The individual user estimates the timing offset using the ESPRIT algorithm, and thereafter
Figure BDA00023545055800000914
The method for estimating the timing offset of each user is used to obtain the timing offset of the user
Figure BDA00023545055800000915
Individual user setting matrix
Figure BDA00023545055800000916
Wherein each column vector of the matrix V corresponds to RzIs/are as follows
Figure BDA00023545055800000917
The characteristic vectors are arranged, wherein the characteristic values corresponding to the characteristic vectors are arranged from big to small;
thereby re-acquiring the effective timing offset of the estimated user using the ESPRIT algorithm;
Figure BDA0002354505580000101
wherein
Figure BDA0002354505580000102
Is a matrix
Figure BDA0002354505580000103
Characteristic value of (V)1And V2Respectively, are formed by the first N-1 row and the last N-1 row of the matrix V, and the estimated timing offset is noted as
Figure BDA0002354505580000104
Figure BDA0002354505580000105
The effective frequency domain code is recorded as
Figure BDA0002354505580000106
For the rest
Figure BDA0002354505580000107
Each user is set to have a timing offset of
Figure BDA0002354505580000108
Solving the timing offset for each remaining user according to a system of equations
Figure BDA0002354505580000109
Where H represents the transpose of the matrix,
Figure BDA00023545055800001010
because Z has N column vectors, the maximum number of the above equation is N-1, so theoretically, the maximum number of N-1 users can be estimated by using the method, and compared with the method only using an MDL algorithm, the estimated number of users is doubled. Recording timing offset and effective frequency domain code of all estimated users
Figure BDA00023545055800001011
Figure BDA00023545055800001012
Where T represents the transpose of the matrix.
Step 3.2: acquiring a frequency domain resource code selected by a user by using the obtained timing offset estimation value;
maximum value of timing error thetamaxIf the condition is satisfied
Figure BDA0002354505580000111
Then ekAnd (l)k,θk) Can be expressed as:
lk＝ceil(N∈k) (2)
Figure BDA0002354505580000112
wherein, according to the ceil (·) function expression, the minimum integer which is larger than or equal to the designated expression is returned, and according to the formula (2), the timing offset obtained in the step 3.1 is used to obtain the frequency domain code of the estimated user;
and 4, step 4: the base station end estimates the channel response of the user, and the process is as follows:
step 4.1: acquiring a channel response estimation value of an estimation user by using the parameters acquired in the step 3;
Figure BDA0002354505580000113
where represents the conjugate of the matrix, | | | · | |, represents the euclidean norm;
step 4.2: judging whether there is an estimated value in step 3 according to the channel response estimated value
Figure BDA0002354505580000114
Where H represents the conjugate transpose of the matrix, if
Figure BDA0002354505580000115
Explaining the effective offset error of the estimated user k, respectively recording the offset estimation values of the users with correct estimation and the users with wrong estimation, and recording the number of the users with correct estimation as
Figure BDA0002354505580000116
The number of users estimated by error is
Figure BDA0002354505580000117
A plurality of;
step 4.3: if there is a user with error estimation, re-estimating the timing offset and frequency domain code for the user with error estimation, and recording the timing offset of the re-estimated user as
Figure BDA0002354505580000118
Step 4.4: acquiring the channel response estimation values of all estimated users again, recording the users which can be successfully detected, judging whether users needing to be retransmitted exist or not, and recording the channel response estimation values after re-estimation as
Figure BDA0002354505580000119
Computing
Figure BDA0002354505580000121
Where H represents the conjugate transpose of the matrix if NumkThe sum of each row element in the user data is more than 1, which indicates that a plurality of users have similar offsets with the user and the model is difficult to distinguish, so user retransmission is needed, and the number of the users UE which can be correctly detected is recordedsuccess1And retransmits the user to be retransmitted,
and 5: and for the retransmission user base station, performing second channel response estimation, wherein the process is as follows:
step 5.1: repeating the steps 2-4.3 for the users needing to be retransmitted in the step 4.4;
step 5.2: for retransmissionThe user obtains the channel response estimated value, and records the user number UE which can be successfully detected after retransmissionsuccess2；
Step 5.3: recording the user, UE successfully detected in step 4.4 and step 5.2success＝UEsuccess1+UEsuccess2Total number of successfully detected users;
step 6: the random access procedure ends.
The invention is further described below in conjunction with the simulation diagrams.
1. Simulation conditions are as follows:
the invention was subjected to simulation experiments using the software simulation platform Matlab R2016 a. The results are shown in FIGS. 2 and 3. The simulation parameters of the invention are set as follows: the time domain resource block number Q is 2, and the frequency domain resource block number is provided with two contrast values N8 and N10. The total number of antennas M of the base station is 500, and the number of users in the cell is 800.
2. Simulation content and result analysis:
fig. 2 is a relationship between the detection probability of active users and the number of antennas at the base station side according to the present invention. The abscissa of fig. 2 represents the number of antennas at the base station side, and the detection probability of the active user is represented from the coordinate. According to the curve change, we can find that the detection probability of the user increases gradually with the increase of the number of the antennas, and the detection probability when the frequency domain resource block N is 10 is obviously higher than that when N is 8. Fig. 3 is a relationship between the detection probability of an active user and the number of users in a cell according to the present invention. The abscissa of fig. 3 represents the total number of users in a cell, and the ordinate represents the probability of active user detection. It can be seen that the user detection probability decreases with the increase of the number of users in the cell, but based on the simulation result, when the number of users reaches 1300, the detection probability can still reach about 70%, where the detection probability when the frequency domain resource block N is 10 is obviously higher than that when N is 8.

Claims (6)

1. A random access method based on massive MIMO is characterized by comprising the following steps:
step 1: for a user who wants to access a network in a cell, the user respectively selects codes from time domain resources and frequency domain resources to form a time domain and frequency domain random access block and sends a random access request to a base station;
step 2: the base station estimates the number of the activated users who select the same time domain resource at present, and the process is as follows;
step 2.1: a base station receives a received signal matrix of an activated user;
step 2.2: associating the received signal matrix with the current time domain resource, and estimating the number of users selecting the current time domain resource;
and step 3: performing frequency domain resource code identification and timing offset estimation on all users, wherein the process comprises the following steps:
step 3.1: estimating timing offset of all estimated users by using a method for estimating timing offset
Step 3.2: acquiring a frequency domain resource code selected by a user by using the obtained timing offset estimation value;
and 4, step 4: the base station end estimates the channel response of the user, and the process is as follows;
step 4.1: acquiring a channel response estimation value of an estimation user by using the parameters acquired in the step 3;
step 4.2: judging whether an error estimation value exists in the step 3 according to the channel response estimation value;
step 4.3: if the user with the wrong estimation exists, the timing offset and the frequency domain code of the user are estimated again;
step 4.4: acquiring channel response estimation values of all estimated users again, recording the users which can be successfully detected, and judging whether users needing to be retransmitted exist or not;
and 5: performing second channel response estimation on the retransmission user base station;
step 5.1: repeating the steps 2-4.3 for the users needing to be retransmitted in the step 4.4;
step 5.2: acquiring a channel response estimation value aiming at a retransmission user, and recording the number of users which can be successfully detected after retransmission;
step 5.3: recording the users successfully detected in the step 4.4 and the step 5.2;
step 6: the random access procedure ends.
2. The massive MIMO-based random access method according to claim 1, wherein in step 1, for the active user-selectable random access block, it is composed of Q consecutive OFDM symbols and N adjacent subcarriers, which total to τ samples, where τ is QN.
3. A massive MIMO based random access method according to claim 1 or 2, wherein in step 2, since the orthogonality of the time domain codes is not destroyed by the propagation channel, the users selecting different time domain codes will not interfere with each other.
4. The massive MIMO-based random access method as claimed in claim 1 or 2, wherein in step 2, the base station obtains the received signal as
Figure FDA0002354505570000021
Which represents the DFT output matrix for the mth antenna of the base station,
Figure FDA0002354505570000022
associated with the current time domain resource, the user number of the current time domain resource can be estimated
Figure FDA0002354505570000023
5. The massive MIMO-based random access method as claimed in claim 1 or 2, wherein in the step 3, before performing timing offset estimation and frequency domain code identification on the estimated users, the number of estimated users needs to be determined
Figure FDA0002354505570000024
Size relation with N-1, for less than or equal to N-1 users and more than N-1 partAnd the user respectively adopts different algorithms to estimate the timing offset of the user, and obtains the frequency domain coding of the user through the timing offset.
6. The massive MIMO-based random access method according to claim 1 or 2, wherein in step 4.4, if there are two or more users with the same random access block and the timing offsets thereof are very small, the model will be difficult to distinguish between the two users, so according to the estimated user channel information, it can be determined whether there are multiple users that cannot be distinguished, record the users that cannot be distinguished and resend them, the retransmitted user repeats steps 1 to 4, and finally the base station re-estimates the channel response of the retransmitted user.
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